Name
Abstract | ||
|---|---|---|
For tree-based partitioning algorithms that lead to Takagi-Sugeno fuzzy models the optimization of the consequents part goes hand in hand with the optimization of the premises part. The prediction performance can significantly be improved with the application of subset selection methods for the local polynomial models. Traditionally, the subset selection methods are applied after the model structure is already optimized. The main idea and new contribution of this work is the implementation of a so called structure trade-off procedure which allows to automatically find a good compromise between the number of local models and the flexibility of the local polynomial rule consequents. The main innovation of this approach is that the structure optimization and variable selection can be performed at the same time. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/CCA.2012.6402404 | Control Applications |
Keywords | Field | DocType |
computational complexity,fuzzy systems,optimisation,polynomials,tree data structures,Takagi-Sugeno fuzzy models,local model networks,local polynomial models,local polynomial rule consequents,prediction performance improvement,structure optimization,structure trade-off strategy,subset selection methods,tree-based partitioning algorithms,variable selection | Mathematical optimization,Feature selection,Polynomial,Computer science,Fuzzy logic,Tree (data structure),Trade-off,Fuzzy control system,Computational complexity theory | Conference |
ISSN | ISBN | Citations |
1085-1992 E-ISBN : 978-1-4673-4504-0 | 978-1-4673-4504-0 | 1 |
PageRank | References | Authors |
0.35 | 6 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Benjamin Hartmann | 1 | 25 | 2.31 |
| Oliver Nelles | 2 | 99 | 17.27 |